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NASA NTRS2019

Target Optimal Aperture Selection

This document describes the computation of optimal pixels for planetary transit targets. The method we describe is based on that used in the End-to-End Model (ETEM), which simulates Kepler science output. An optimal aperture for a target is defined as the set of pixels which maximizes the signal-to-noise ratio (SNR) for that target. The optimal aperture for a target is determined by using catalog data to generate, for that target, a synthetic image with all background stars and signals and a second synthetic image with the target star's flux only. These images are incorporated into a noise model, from which the SNR of each pixel is computed. The pixels around a target are summed in an order that maximizes the SNR with each term. As dimmer and dimmer pixels contribute to this sum, the SNR reaches a maximum and further terms decrease the SNR. The set of pixels whose SNR sums to this maximum value defines the optimal aperture.

Bryson, Stephen↗
NASA NTRS2019

A Robust Vision-Based Algorithm for Detecting and Classifying Small Orbital Debris Using On-Board Optical Cameras

This study develops a vision-based detection and classification algorithm to address the challenges of in-situ small orbital debris environment classification including debris observability and instrument requirements for small debris observation. The algorithm operates in near real time and is robust under difficult tasks in moving objects classification such as multiple moving objects, objects with various movement trajectories and speeds, very small or faint objects, and substantial background motion. The performance of the algorithm is optimized and validated using space image data available through simulated environments generated using NASA Marshall Space Flight Centers Dynamic Star Field Simulator of on-board optical sensors and cameras.

Zamani, Yasin↗
NASA NTRS1995

Orbiting Stellar Interferometer: An Overview

The Orbiting Stellar Interferometer (OSI) is a concept for a first-generation space interferometer with astrometric and imaging capabilities and is responsive to the recommendations of the Astronomy and Astrophysics Survey Committee for an astrometric interferometry mission. OSI is a triple Michelson interferometer with articulating siderostats and optical delay lines. The design uses a 7m maximum baseline and aperture diameters of 33 cm; the targeted astrometric performance is a wide-field accuracy of 5µas for 20-mag objects. The instrument would also be capable of synthesis imaging with a resolution of 10mas. Laser metrology is used to relax structural requirements thereby reducing cost. The currently envisaged flight system fits into an Atlas II shroud, for insertion into a 900 km sun-synchronous orbit.

['OSI↗
NASA NTRS2020

The Wide-field VLBA Calibrator Survey: WFCS

This paper presents the results of the largest very long baseline interferometry (VLBI) absolute astrometry campaign to date of 13,645 radio source observations with the Very Long Baseline Array. Of these, 7220 have been detected, including 6755 target sources that have never been observed with VLBI before. This makes the present VLBI catalog the largest ever published. The positions of the target sources have been determined with the median uncertainty of 1.7 mas, and 15,542 images of 7171 sources have been generated. Unlike previous absolute radio astrometry campaigns, observations were made at 4.3 and 7.6 GHz simultaneously using a single wide-band receiver. Because of the fine spectral and time resolutions, the field of view was 4'–8'—much greater than the 10''–20'' in previous surveys. This made possible the use of input catalogs with low position accuracy and the detection of a compact component in extended sources. Unlike previous absolute astrometry campaigns, both steep- and flat-spectrum sources were observed. The observations were scheduled in the so-called filler mode to fill the gaps between other high-priority programs. This was achieved by the development of the totally automatic scheduling procedure.

Leonid Petrov↗
NASA NTRSDate not supplied

Validation of Rendered Natural and Artificial Lighting Environments in Real Time Lunar South Pole Simulations

NASA’s Artemis campaign is making heavy use of simulation to help return humans to the lunar surface by the end of the decade. There are several aspects of the lunar surface and its environment which must be accurately modeled before these simulations can be relied upon to influence decisions being made under these programs. Digital Lunar Exploration Sites, a paper submitted to the 2022 IEEE Aerospace Conference, outlined the process used to generate the lunar surface in a digital environment. This paper will expand upon this topic and delve into the steps being taken by the NASA Exploration Systems Simulations (NExSyS) team at NASA’s Johnson Space Center (JSC) to properly verify and validate these simulations, with a focus on the visual aspects of the environment. Natural lighting validation relies in part on the wealth of data generated during the Apollo program. Many images taken by Apollo astronauts on the lunar surface have been replicated in the simulated environments to gain confidence in the accuracy of terrain and lighting models. However, because the environment the Artemis astronauts will experience at the Lunar South Pole (LSP) is dissimilar from the near-equatorial Apollo sites, other validation techniques must be applied. At the LSP, the sun crests only about three degrees above the horizon and when combined with the lack of a lunar atmosphere, lighting in this region is often very different than what a human would experience on Earth. Solar illumination, earthshine, human eye response, solar blooming, lunar regolith optical properties, and shadows cast by rocks and crater walls will play a significant role in an astronaut’s ability to safely conduct an Extra-Vehicular Activity (EVA) or perform a traverse with a lunar rover. Approaches for validation of these aspects of the rendered LSP environment are considered in this paper. In addition to natural lighting, approaches for the validation of artificial lighting models at the LSP are discussed. The JSC Lighting Lab has been studying the illumination profile of the Exploration Infomatics Subsystem (xINFO) lighting on the Exploration EVA Mobility Unit (xEMU). How these lights interact with the solar illumination and the shadows being cast on the lunar surface is of particular interest, so the validity of models representing these lights in a human-in-the-loop virtual reality environment becomes very important. This paper also touches on some of the simulation performance considerations when a Human in the Loop (HITL) is present, which drives the need for real time rendering of the environment. Natural and artificial lighting will play a crucial role to decisions being made when planning and executing missions at the Lunar South Pole (LSP) and it is vitally important to understand the LSP environment before we return.

Lunar↗
NASA NTRSDate not supplied

Development of a Consistent Cross-Platform GEO-Satellite Cloud Mask to Support CERES

Geostationary satellites provide continuous cloud and meteorological observations over a fixed portion of the Earth’s surface, allowing them to monitor the movement of storm systems and their diurnal variation. For climate studies, geostationary observations provide valuable insight of cloud formation and evolution and how they influence the Earth’s radiation budget. The Geo-Satellite Edition 4 cloud mask (GEO Ed4) is used operationally in NASA’s Cloud and Earth’s Radiant Energy System (CERES) project to help account for diurnal variations in cloudiness on Earth’s radiation budget. The Ed4 cloud mask was applied to imager data on MSG (MeteoSat Second Generation), Himawari, GOES-West, and GOES-East satellites using as much spectral information as possible. That approach led to some discontinuities when a more modern satellite replaced an older satellite with less spectral information. A different strategy is being investigated for the CERES GEO Ed5 cloud mask that only uses spectral channels common on every satellite. Thus, a 3-channel (0.6, 3.9, 11 µm) algorithm for daytime cloud detection, and a 2-channels (3.9 and 11 µm) algorithm for nighttime cloud detection have been implemented and tested for Ed5. The goal of Ed5 cloud mask is to achieve global cloud amount consistency across five geo-satellites, and a smooth transition from an old satellite to a new satellite over each geo-location. This paper compares cloud mask results between Ed4 and a preliminary Ed5 version over the GOES-East region, using GOES-8, GOES-13, and GOES-16 satellites, each with a different spectral channel complement. Instantaneous and monthly regional mean inter-comparisons are performed and evaluated with CALIPSO cloud products to assess the accuracy and consistency of the Ed5 approach relative to that taken in Ed4. Results will be presented and discussed at the conference.

clouds↗
NASA NTRS2023

Approaches for Validation of Lighting Environments in Realtime Lunar South Pole Simulations

NASA’s Artemis campaign is making heavy use of simulation to help return humans to the lunar surface by the end of the decade. There are several aspects of the lunar surface and its environment which must be accurately modeled before these simulations can be relied upon to influence decisions being made under these programs. Digital Lunar Exploration Sites, a paper submitted to the 2022 IEEE Aerospace Conference, outlined the process used to generate the lunar surface in a digital environment. This paper will expand upon this topic and delve into the steps being taken by the NASA Exploration Systems Simulations (NExSyS) team at NASA’s Johnson Space Center (JSC) to properly verify and validate these simulations, with a focus on the visual aspects of the environment. Natural lighting validation relies in part on the wealth of data generated during the Apollo program. Many images taken by Apollo astronauts on the lunar surface have been replicated in the simulated environments to gain confidence in the accuracy of terrain and lighting models. However, because the environment the Artemis astronauts will experience at the Lunar South Pole (LSP) is dissimilar from the near-equatorial Apollo sites, other validation techniques must be applied. At the LSP, the sun crests only about 1.5 degrees above the horizon and when combined with the lack of a lunar atmosphere, lighting in this region is often very different than what a human would experience on Earth. Solar illumination, earthshine, human eye response, solar blooming, lunar regolith optical properties, and shadows cast by rocks and crater walls will play a significant role in an astronaut’s ability to safely conduct an Extra-Vehicular Activity (EVA) or perform a traverse with a lunar rover. Approaches for validation of these aspects of the rendered LSP environment are considered in this paper. In addition to natural lighting, approaches for the validation of artificial lighting models at the LSP are discussed. The JSC Lighting Lab has been studying the illumination profile of the Exploration Informatics Subsystem (xINFO) lighting on the Exploration EVA Mobility Unit (xEMU). How these lights interact with the solar illumination and the shadows being cast on the lunar surface is of particular interest, so the validity of models representing these lights in a human-in-the-loop virtual reality environment becomes very important. This paper also touches on some of the simulation performance considerations when a Human in the Loop (HITL) is present, which drives the need for realtime rendering of the environment. Natural and artificial lighting will play a crucial role to decisions being made when planning and executing missions at the Lunar South Pole (LSP) and it is vitally important to understand the LSP environment before we return.

Lunar↗
NASA NTRS2019

TESS Science Processing Operations Center Pipeline and Data Products

TESS launched 18-4-2018 to conduct a two-year, near all-sky survey for at least 50 nearby exoplanets for which masses can be. TESS just completed surveying the southern hemisphere, identifying hundreds of candidate exoplanet systems and unveiling a plethora of exciting non-exoplanet astrophysics results, such as asteroseismology, asteroids, and supernova. The TESS Science Processing Operations Center (SPOC) at NASA Ames Research Center processes the image data downlinked from TESS every two weeks to generate a variety of data products hosted at the Mikulski Archive for Space Telescopes (MAST). For each ~1 month sector, the SPOC calibrates the image data for both 30-min Full Frame Images (FFIs) and up to 20,000 pre-selected 2-min target star postage stamps. Simple aperture photometry and systematic error-corrected flux time series are generated for the 2-min data. The data products also include co-trending basis vectors (CBVs) and calibration files, such as the Pixel Response Functions (PRF). The archival files are modeled after Kepler's for ease of use, and include Target Pixel Files (TPFs) containing original and calibrated 2-min image data, Light Curve files (LCs) containing the photometric time series for each 2-min target, as well as the Data Validation products. New products derived from the FFIs include light curves for the 2-min targets and CBVs. The TESS Mission is funded by NASA's Science Mission Directorate as an Astrophysics Explorer Mission.

Jenkins, Jon M.↗
NASA NTRS2017

Automated Mapping of Flood Events in the Mississippi River Basin Utilizing NASA Earth Observations

The Mississippi River Basin is the fourth largest drainage basin in the world, and is susceptible to multi-level flood events caused by heavy precipitation, snow melt, and changes in water table levels. Conducting flood analysis during periods of disaster is a challenging endeavor for NASA's Short-term Prediction Research and Transition Center (SPoRT), Federal Emergency Management Agency (FEMA), and the U.S. Geological Survey's Hazards Data Distribution Systems (USGS HDDS) due to heavily-involved research and lack of manpower. During this project, an automated script was generated that performs high-level flood analysis to relieve the workload for end-users. The script incorporated Landsat 8 Operational Land Imager (OLI) tiles and utilized computer-learning techniques to generate accurate water extent maps. The script referenced the Moderate Resolution Imaging Spectroradiometer (MODIS) land-water mask to isolate areas of flood induced waters. These areas were overlaid onto the National Land Cover Database's (NLCD) land cover data, the Oak Ridge National Laboratory's LandScan data, and Homeland Infrastructure Foundation-Level Data (HIFLD) to determine the classification of areas impacted and the population density affected by flooding. The automated algorithm was initially tested on the September 2016 flood event that occurred in Upper Mississippi River Basin, and was then further tested on multiple flood events within the Mississippi River Basin. This script allows end users to create their own flood probability and impact maps for disaster mitigation and recovery efforts.

Bartkovich, Mercedes↗
NASA NTRS2000

BOREAS TE-17 Production Efficiency Model Images

A Boreal Ecosystem-Atmospheric Study (BOREAS) version of the Global Production Efficiency Model (http://www.inform.umd.edu/glopem/) was developed by TE-17 (Terrestrial Ecology) to generate maps of gross and net primary production, autotrophic respiration, and light use efficiency for the BOREAS region. This document provides basic information on the model and how the maps were generated. The data generated by the model are stored in binary image-format files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗
NASA NTRS2019

TESS Science Processing Operations Center Pipeline and Data Products

TESS (Transiting Exoplanet Survey Satellite) launched on 18-4-2018 to conduct a two-year, near all-sky survey for at least 50 nearby exoplanets for which masses can be obtained. TESS just completed surveying the southern hemisphere, identifying hundreds of candidate exoplanet systems and unveiling a plethora of exciting non-exoplanet astrophysics results, such as asteroseismology, asteroids, and supernova. The TESS Science Processing Operations Center (SPOC) at NASA Ames Research Center processes the image data downlinked from TESS every two weeks to generate a variety of data products hosted at the Mikulski Archive for Space Telescopes (MAST). For each approximately 1-month sector, the SPOC calibrates the image data for both 30-minute Full Frame Images (FFIs) and up to 20,000 pre-selected 2-minute target star postage stamps. Simple aperture photometry and systematic error-corrected flux-time series are generated for the 2-minute data. The data products also include co-trending basis vectors (CBVs) and calibration files, such as the Pixel Response Functions (PRF). The archival files are modeled after Kepler's for ease of use, and include Target Pixel Files (TPFs) containing original and calibrated 2-minute image data, Light Curve files (LCs) containing the photometric time series for each 2-minute target, as well as the Data Validation products. New products derived from the FFIs include light curves for the 2-minute targets and CBVs. The TESS Mission is funded by NASA's Science Mission Directorate as an Astrophysics Explorer Mission.

Science Pipeline↗
NASA NTRS1992

Wavelength tunable liquid crystal imaging filters for remote sensing from geosynchronous platforms

Recent advances in liquid crystal technology have enabled us to construct tunable birefringent filters with bandwidths between approximately 0.1 nm and 50 nm. The center wavelength of these filters can be selected electronically, in a few tens of milliseconds, with no moving parts. These liquid crystal tunable filters (LCTF's), together with existing CCD detectors, make possible a new generation of lightweight, rugged, high-resolution imaging spectrophotometers. Such instruments would be particularly interesting for remote sensing applications from geosynchronous platforms. Important advantages exist in the aperture, absence of image shift, power consumption, size, weight, and absence of high drive frequencies, compared to current instruments used or considered for multispectral scene analysis. In the present work, we have reviewed spectral requirements of planned NASA geosynchronous remote sensing missions and identified several applications of the liquid crystal tunable filter technology. We have modeled the LCTF performance in the visible and near-infrared, and carried out a literature study on space-hardening of the filter components, to evaluate the suitability of LCTF's for geosynchronous missions. We have also compared the power consumption, weight, size, reliability, and optical performance of an imaging spectrophotometer using a LCTF monochromator, to other instruments that have been put forward for remote sensing from geosynchronous platforms. We put forward some conceptual designs for LCTF's that seem to offer important reliability, over the mechanical filter wheels presently baselined for the HEPI and ALM experiments. The extremely wide acceptance angle achievable with LCTF's could also avoid the present need for large-aperture interference filters in the ALM (and LIS) experiments. Thermal vacuum testing and radiation damage analysis is required to investigate the space hardening of these new filters for geosynchronous flight.

Foukal, Peter↗
NASA NTRSDate not supplied

Radiometric Assessment of the First Three Years of the NOAA-20 VIIRS Reflective Solar Bands Calibration

NASA’s Clouds and the Earth’s Radiant Energy System (CERES) SYN1deg Ed4.1 product utilizes geostationary (GEO) satellite measured radiances and retrieved cloud properties to account for the regional diurnal fluctuations in the Earth’s radiant broadband fluxes for times between the CERES measurements gathered from the Aqua (1:30 PM) and Terra (10:30 AM) sun-synchronous satellites. In CERES Edition 4 products, a global uniformity in the cloud properties and computed surface fluxes across the GEO satellite domains is maintained by scaling the radiance observations from more than twenty GEO visible imagers in the CERES record to a common radiometric reference scale, i.e., Aqua-MODIS. With the new-generation GEO (Himawari-8/9 and GOES-16/17) imagers having multiple reflective solar bands (RSB) that are spectrally similar to those of VIIRS, the CERES Imager and Geostationary Calibration Group (IGCG) is preparing to use NOAA-20 VIIRS as the reference imager for maintaining the radiometric uniformity across the GEO imager constellation. Given the recent Aqua satellite anomaly, this transition may happen sooner than the projected date of Aqua’s de-orbit. This paper presents an independent performance evaluation of the first three years of the NOAA-20 VIIRS RSB calibration in the NASA VIIRS Land Science Investigator-led Processing System (Land SIPS) L1b Collection 2 dataset. The temporal radiometric stability is assessed using multiple invariant Earth targets, including tropical deep convective clouds and the Saharan desert. The invariant target anisotropic reflectance at the top of atmosphere was modeled using five years of stable satellite observations acquired from the previous VIIRS instrument onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite. The anisotropic corrections are essential for detecting temporal trends with a high statistical confidence. In addition, the radiometric consistency between the RSB of the two VIIRS instruments will be evaluated.

Rajendra Bhatt↗
NASA NTRSDate not supplied

Radiometric Assessment of the First Three Years of the NOAA-20 VIIRS Reflective Solar Bands Calibration

NASA’s Clouds and the Earth’s Radiant Energy System (CERES) SYN1deg Ed4.1 product utilizes geostationary (GEO) satellite measured radiances and retrieved cloud properties to account for the regional diurnal fluctuations in the Earth’s radiant broadband fluxes for times between the CERES measurements gathered from the Aqua (1:30 PM) and Terra (10:30 AM) sun-synchronous satellites. In CERES Edition 4 products, a global uniformity in the cloud properties and computed surface fluxes across the GEO satellite domains is maintained by scaling the radiance observations from more than twenty GEO visible imagers in the CERES record to a common radiometric reference scale, i.e., Aqua-MODIS. With the new-generation GEO (Himawari-8/9 and GOES-16/17) imagers having multiple reflective solar bands (RSB) that are spectrally similar to those of VIIRS, the CERES Imager and Geostationary Calibration Group (IGCG) is preparing to use NOAA-20 VIIRS as the reference imager for maintaining the radiometric uniformity across the GEO imager constellation. Given the recent Aqua satellite anomaly, this transition may happen sooner than the projected date of Aqua’s de-orbit. This paper presents an independent performance evaluation of the first three years of the NOAA-20 VIIRS RSB calibration in the NASA VIIRS Land Science Investigator-led Processing System (Land SIPS) L1b Collection 2 dataset. The temporal radiometric stability is assessed using multiple invariant Earth targets, including tropical deep convective clouds and the Saharan desert. The invariant target anisotropic reflectance at the top of the atmosphere was modeled using five years of stable satellite observations acquired from the previous VIIRS instrument onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite. The anisotropic corrections are essential for detecting temporal trends with high statistical confidence. In addition, the radiometric consistency between the RSB of the two VIIRS instruments will be evaluated.

Rajendra Bhatt↗
NASA NTRS2021

The Dark Side of Pluto

During its departure from Pluto, New Horizons used its LORRI camera to image a portion of Pluto's southern hemisphere that was in a decades-long seasonal winter darkness, but still very faintly illuminated by sunlight reflected by Charon. Recovery of this faint signal was technically challenging. The bright ring of sunlight forward-scattered by haze in the Plutonian atmosphere encircling the nightside hemisphere was severely overexposed, defeating the standard smeared-charge removal required for LORRI images. Reconstruction of the overexposed portions of the raw images, however, allowed adequate corrections to be accomplished. The small solar elongation of Pluto during the departure phase also generated a complex scattered-sunlight background in the images that was three orders of magnitude stronger than the estimated Charon-light flux (the Charon-light flux is similar to the flux of moonlight on Earth a few days before first quarter). A model background image was constructed for each Pluto image based on principal component analysis applied to an ensemble of scattered-sunlight images taken at identical Sun−spacecraft geometry to the Pluto images. The recovered Charon-light image revealed a high-albedo region in the southern hemisphere. We argue that this may be a regional deposit of N2 or CH4 ice. The Charon-light image also shows that the south polar region currently has markedly lower albedo than the north polar region of Pluto, which may reflect the sublimation of N2 ice or the deposition of haze particulates during the recent southern summer.

Pluto↗
NASA NTRS2004

Knowledge Driven Image Mining with Mixture Density Mercer Kernels

This paper presents a new methodology for automatic knowledge driven image mining based on the theory of Mercer Kernels; which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly infinite dimensional feature space. In that high dimensional feature space, linear clustering, prediction, and classification algorithms can be applied and the results can be mapped back down to the original image space. Thus, highly nonlinear structure in the image can be recovered through the use of well-known linear mathematics in the feature space. This process has a number of advantages over traditional methods in that it allows for nonlinear interactions to be modelled with only a marginal increase in computational costs. In this paper, we present the theory of Mercer Kernels, describe its use in image mining, discuss a new method to generate Mercer Kernels directly from data, and compare the results with existing algorithms on data from the MODIS (Moderate Resolution Spectral Radiometer) instrument taken over the Arctic region. We also discuss the potential application of these methods on the Intelligent Archive, a NASA initiative for developing a tagged image data warehouse for the Earth Sciences.

Srivastava, Ashok N.↗
NASA NTRS2004

Knowledge Driven Image Mining with Mixture Density Mercer Kernals

This paper presents a new methodology for automatic knowledge driven image mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly infinite dimensional feature space. In that high dimensional feature space, linear clustering, prediction, and classification algorithms can be applied and the results can be mapped back down to the original image space. Thus, highly nonlinear structure in the image can be recovered through the use of well-known linear mathematics in the feature space. This process has a number of advantages over traditional methods in that it allows for nonlinear interactions to be modelled with only a marginal increase in computational costs. In this paper we present the theory of Mercer Kernels; describe its use in image mining, discuss a new method to generate Mercer Kernels directly from data, and compare the results with existing algorithms on data from the MODIS (Moderate Resolution Spectral Radiometer) instrument taken over the Arctic region. We also discuss the potential application of these methods on the Intelligent Archive, a NASA initiative for developing a tagged image data warehouse for the Earth Sciences.

Srivastava, Ashok N.↗